Extended Kalman Filter-based localization algorithm by edge computing in Wireless Sensor Networks

The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both the system and the estimation model.Also,in the field of engineering,most systems are non-linear.Therefore,the EKF attracts more attention than the Kalman Filter(KF).In this paper,we propose an EKF-based localization algorithm by edge computing,and a mobile robot is used to update its location concerning the landmark.This localization algorithm aims to achieve a high level of accuracy and wider coverage.The proposed algorithm is helpful for the research related to the use of EKF localization algorithms.Simulation results demonstrate that,under the situations presented in the paper,the proposed localization algorithm is more accurate compared with the current state-of-the-art localization algorithms.

具有未知参数的机器人-摄像机系统的自适应动态反馈跟踪控制（英文）

The tracking problem of nonholonomic mobile robots with uncertainties is investigated in this paper. An uncertain model of the nonholonomic kinematic system is presented based on the visual feedback and the state and input transformations for a kind of mobile robots in chained form with uncertainties. Two transformations are exploited based on the idea of backstepping and the structure of tracking error system. Then, both an adaptive control law and a dynamic feedback robust controller are designed to track the desired trajectory by using Lyapunov direct method and the extended Barbalat Lemma. The asymptotic convergence of a closed-loop error system is proved rigorously. Finally, simulation results demonstrate the effectiveness of the proposed strategies.

Responses and stability of power system under small Gauss type random excitation

With the integration of renewable power and electric vehicle,the power system stability is of increasing concern because the active power generated by the renewable energy and absorbed by the electric vehicle vary randomly.Based on the deterministic differential equation model,the nonlinear and linear stochastic differential equation models of power system under Gauss type random excitation are proposed in this paper.The angle curves under different random excitations were simulated using Euler-Maruyama(EM) numerical method.The numerical stability of EM method was proved.The mean stability and mean square stability of the power system under Gauss type of random small excitation were verified theoretically and illustrated with simulation sample.

A NEUROENDOCRINE-INSPIRED BIONIC MANUFACTURING SYSTEM

Due to rapid changes of markets and pressures of competitions, the manufacturing companies are forced to adapt their production ways to support diversity of customer＇s needs and increase of new product developments. As biological organisms are quite capable of adapting to environmental changes and stimulus, bio-inspired concepts have been recognized much suitable for adaptive manufacturing system control. This paper, therefore, proposes a novel concept of NeuroEndocrine-Inspired Manufacturing System （NEIMS）. The proposed NEIMS control architecture is based on analogies with neuro-control and hormone-regulation principles. It has the capability to explicitly specify production control schemes including control points, material, information flow paths and logical operations, and to agilely deal with the frequent occurrence of unexpected disturbances at the shop floor level. From the cybernetics point of view, the control model of NEIMS indicates adaptive behavior to the changes in products demands due to external environment and malfunction of manufacturing cells as an intemal environment. Finally, a prototype system has been set up to enable the NEIMS simulation.

A SELFISH ROUTING BASED NETWORK IMPROVEMENT PROBLEM

这篇论文考虑自私路由基于网络改进问题，作者想在发现导致新纳什平衡流动的一个修改潜伏函数令人满意所有交通要求题目到目标能力，当全部的修正花费了时紧张不安潜伏被最小化。由从 3 可满足性(3-SAT ) 使用减小问题到我们的问题，作者证明这个问题是强烈 NP 难的，甚至为单个商品网络。

Modeling the Damage and Self-healing Behaviors of Plasticized PVC Gels

Plasticized polyvinyl chloride(PVC)gel is a type of electroactive polymers,which has potentials to be applied as soft actuators.However,few studies have been performed to investigate the mechanical responses of PVC gels in cyclic loading conditions.In this work,we combined experiments and theory to characterize the mechanical responses of two plasticized PVC gels.The gels were subjected to different types of loading-unloading-reloading cycles.The experimental results showed that the plasticized PVC gels exhibited stress softening response(the Mullins effect)in the cyclic tests.Meanwhile,the gels regained some strength after annealing at room temperature for several hours,indicating the self-healing ability of gels.We further extended the eight-chain model with incorporation of the chain dissociation and reassociation mechanism.The developed constitutive model is able to reproduce the Mullins effect and the recovery of the Mullins effect observed in the experiments.Our results clearly show that understanding the complex mechanical response is crucial for the applications of plasticized PVC gels.